Effect Of Text Reviews And Reviews Volume On Product Sales Under The Improved Text Mining Method

With the popularization of e-commerce,the research about Online Consumer Reviews has experienced a process from easy to difficult.In recent years,due to the improvement of text mining technology,more and more scholars have turned their attention to text reviews.However,there are contradictory conclusions in the current study of the impact of text reviews on sales,which is likely due to unreasonable text classification.Text classification depends on accurate sentiment analysis methods,but the current Chinese sentiment analysis method needs further improvement.This article uses the big data mining tool Python to capture 12,278,861 pieces of data from 109 tablets.Basing on the theory of optimal arousal theory,dilution effect,bandwagon effect,persuasive effect and awareness effect,and according to 839 consumers online review browsing path questionnaire survey results,this paper uses the dynamic Panel model to regress the data.In order to improve the accuracy of text classification,this paper improves the text mining technology from three aspects,the selection of word segmentation tools,the expansion of the thesaurus,and the classification of text comments.Through the choice of word segmentation tools and the expansion of word banks,the accuracy of text assignments is improved.Through the using of two-dimensional text classification methods and according to consumer online shopping practices,the value range of neutral text reviews is expanded,and the science of text classification is improved.Online text reviews have been divided into positive text reviews,mixed positive text reviews,mixed neutral text reviews,indifferent neutral text reviews,mixed negative text reviews,and negative text reviews.Among them,positive text reviews include positive text reviews and mixed positive text reviews.The results show that positive text reviews have a “U”shape relationship with product sales,mixed positive text reviews have a positive impact on product sales.Neutral text reviews include mixed neutral text reviews and indifferent neutral text reviews.The regression results show that mixed neutral text reviews have a positive impact on product sales,while indifferent neutral text reviews have a negative impact on product sales.The negative text reviews include mixed negative reviews and negative text reviews.The results show that mixed negative text reviews have positive impacts on product sales while negative text reviews have negative impacts on product sales.The moderating effect of the number of reviews on the relationship between text reviews and product sales.The results show that the moderating effect of the number of reviews appears to be an increase in product sales.Among them,the number of reviews play a positive moderating effect on the relationship between positive text reviews,mixed neutral text reviews,mixed negative text reviews and product sales,and a negative moderating effect in the relationship between indifferent neutral text reviews and product sales.The research results have certain reference value for explaining the phenomenon of conflicting research conclusions in the current online text reviews research field.At the same time,it has a certain guiding role for the e-commerce platform to maintain online reviews and promote product sales.